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Please use this identifier to cite or link to this item:
https://hdl.handle.net/10119/15419
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| Title: | Simplifying the Auto Regressive and Moving Average (ARMA) Model Representing the Dynamic Thermal Behaviour of iHouse Based on Theoretical Knowledge |
| Authors: | Mohd Hussein, Shamsul Faisal
Abu Bakar, Mohd Anuar
Makino, Yoshiki
Nguyen, Hoaison
Abdullah, Shahrum Shah
Lim, Yuto
Tan, Yasuo |
| Keywords: | Modelling and simulation
black box modelling
building temperature simulation
building temperature prediction |
| Issue Date: | 2017-08-26 |
| Publisher: | Springer |
| Magazine name: | Communications in Computer and Information Science |
| Volume: | 751 |
| Start page: | 697 |
| End page: | 711 |
| DOI: | 10.1007/978-981-10-6463-0_59 |
| Abstract: | Modelling and simulation is an alternative way of testing the dynamic behaviour of a real system – in some situation, testing the real system are expensive, time consuming, not comfortable, and dangerous. Mathematical model describing the dynamic behaviour of a system can be represented by using white, black, or grey box model. This study focuses on developing a simplified Auto Regressive Moving Average (ARMA) model (a type of linear black model) to represent the dynamic thermal behaviour of iHouse – simplification is done based on the theoretical knowledge of the building. The performance of the simplified ARMA model developed in this study is compared with the performance of the models developed in previous studies, which are: (1) House Thermal Simulator; (2) and ARMA model. Result shows that the simplified ARMA model developed in this study consists of simpler set of mathematical equations, but can still simulate the dynamic thermal behaviour of iHouse with the accuracy that is almost on par with the models developed in previous studies. |
| Rights: | This is the author-created version of Springer, Shamsul Faisal Mohd Hussein, Mohd Anuar Abu Bakar, Yoshiki Makino, Hoaison Nguyen, Shahrum Shah Abdullah, Yuto Lim, Yasuo Tan, Communications in Computer and Information Science, 751, 2017, 697-711. The original publication is available at www.springerlink.com, http://dx.doi.org/10.1007/978-981-10-6463-0_59 |
| URI: | https://hdl.handle.net/10119/15419 |
| Material Type: | author |
| Appears in Collections: | b11-1. 会議発表論文・発表資料 (Conference Papers)
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| 23887.pdf | | 726Kb | Adobe PDF | View/Open |
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